Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-28T20:36:52.978Z Has data issue: false hasContentIssue false
  • English
  • Français

Comparative evaluation of anthropometric measures to predict cardiovascular risk factors in Tehranian adult women

Published online by Cambridge University Press:  02 January 2007

Ahmad Esmaillzadeh ,
Parvin Mirmiran  and
Fereidoun Azizi
Ahmad Esmaillzadeh
Affiliation:
Endocrine Research Center, Shaheed Beheshti University of Medical Sciences, PO Box 19 395-4763, Tehran, Islamic Republic of Iran
Parvin Mirmiran
Affiliation:
Endocrine Research Center, Shaheed Beheshti University of Medical Sciences, PO Box 19 395-4763, Tehran, Islamic Republic of Iran
Fereidoun Azizi*
Affiliation:
Endocrine Research Center, Shaheed Beheshti University of Medical Sciences, PO Box 19 395-4763, Tehran, Islamic Republic of Iran
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objective

To compare the ability of waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) to predict cardiovascular risk factors in an urban adult population of Tehranian women.

Design

Population-based cross-sectional study.

Setting

Tehran, the capital of Iran.

Subjects

This study was conducted on 5073 women aged 18–74 years, participants of the Tehran Lipid and Glucose Study. Demographic data were collected. Anthropometric indices were measured according to standard protocols. Cut-off points of BMI, WC, WHR and WHtR were considered as 25 kg m−2, 80 cm, 0.8 and 0.5, respectively. Blood pressure was measured and hypertension was defined based on the sixth report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure. Biochemical analyses were conducted on fasting blood samples. Diabetes was defined as fasting plasma glucose ≥126 mg dl−1 or 2-hour plasma glucose ≥200 mg dl−1 and dyslipidaemia based on the third report of the National Cholesterol Education Program Expert Panel. The presence of ‘at least one risk factor’ from the three major cardiovascular risk factors (hypertension, dyslipidaemia and diabetes) was also evaluated.

Results

Mean (±standard deviation) age of women was 39.9 ± 14.6 years; mean BMI, WC, WHR and WHtR were 27.1 ± 1.5 kg m−2, 86.5 ± 13.5 cm and 0.83 ± 0.08 and 0.55 ± 0.08, respectively. Of the four anthropometric measures, WC had the highest sensitivity and specificity to identify subjects with risk factors in both the 18–39 year and the 40–74 year age categories. WC was seen to have a higher percentage of correct prediction than BMI, WHR and WHtR.

Conclusion

It is concluded that WC is the best screening measure for cardiovascular risk factors, compared with BMI, WHR and WHtR, in Tehranian adult women.

Keywords

Waist circumferenceCardiovascular risk factorsWomenBody mass index
Type
Research Article
Information
Public Health Nutrition , Volume 9 , Issue 1 , February 2006 , pp. 61 - 69
Copyright
Copyright © The Authors 2006

References

1Mokdad, AH, Serdula, MK, Dietz, WH, Bowman, BA, Marks, JS, Koplan, JP. The continuing epidemic of obesity in the United States. Journal of American Medical Association 2000; 284: 1650–1.CrossRefGoogle ScholarPubMed
2Kuczmarski, RJ, Flegal, KM, Campbell, SM, Johnson, CL. Increasing prevalence of overweight among US adults. The National Health and Nutrition Examination Surveys, 1960 to 1991. Journal of American Medical Association 1994; 272: 205–11.CrossRefGoogle ScholarPubMed
3deOnis, M, Blossner, M. Prevalence and trends of overweight among preschool children in developing countries. American Journal of Clinical Nutrition 2000; 72: 1032–9.CrossRefGoogle Scholar
4World Health Organization. Obesity epidemic puts millions at risk from related diseases. Press release WHO/46, 1997 [online]. Available at http//:www.who.int/inf-prp 1997/en/pr97-46.html.Google Scholar
5Pishdad, GR. Overweight and obesity in adults aged 20–74 in southern Iran. International Journal of Obesity and Related Metabolic Disorders 1996; 20: 963–5.Google ScholarPubMed
6Azizi, F, Esmaillzadeh, A, Mirmiran, P. Obesity and cardiovascular risk factors in Tehranian adults: a population-based cross-sectional study. Eastern Mediterranean Health Journal 2004; 10: 887–97.Google Scholar
7World Health Organization (WHO). Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation on Obesity. WHO/NUT/NCD/98.1. Geneva: WHO, 1997.Google Scholar
8Stevens, J, Cai, J, Pamuk, ER, Williamson, DF, Thun, MJ, Wood, JL. The effect of age on the association between body mass index and mortality. New England Journal of Medicine 1998; 338: 1–7.CrossRefGoogle ScholarPubMed
9Wei, M, Gaskill, SP, Haffner, SM, Stern, MP. Waist circumference as the best predictor of non-insulin dependent diabetes mellitus compared to BMI, WHR over other anthropometric measurements in Mexican Americans: a 7-year prospective study. Obesity Research 1997; 5: 16–23.CrossRefGoogle Scholar
10Folsom, AR, Kaye, SA, Sellers, TA, Hong, CP, Cerhan, JR, Potter, JD, et al. Body fat distribution and 5-year risk of death in old women. Journal of American Medical Association 1993; 269: 483–7.CrossRefGoogle Scholar
11Pi-Sunyer, FX. Obesity: criteria and classification. Proceedings of Nutrition Society 2000; 59: 505–9.CrossRefGoogle ScholarPubMed
12Hayashi, T, Boyko, EJ, Leonetti, DL, McNeely, MJ, Newell-Morris, L, Kahn, SE, et al. Visceral adiposity is an independent predictor of incident hypertension in Japanese Americans. Annals of Internal Medicine 2004; 140: 992–1000.CrossRefGoogle ScholarPubMed
13Cox, BD, Whichelow, MJ, Prevost, AT. The development of cardiovascular disease in relation to anthropometric indices and hypertension in British adults. International Journal of Obesity and Related Metabolic Disorders 1998; 22: 966–73.CrossRefGoogle ScholarPubMed
14Pouliot, MC, Despres, JP, Lemieux, S, Moorjani, S, Bouchard, C, Tremblay, A, et al. Waist circumference and abdominal sagittal diameter: best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women. American Journal of Cardiology 1994; 73: 460–8.CrossRefGoogle ScholarPubMed
15Ledoux, M, Lambert, J, Reeder, BA, Despres, JP. A comparative analysis of weight to height and waist to hip circumference indices as indicators of the presence of cardiovascular disease risk factors. Canadian Heart Health Surveys Research Group. Canadian Medical Association Journal 1997; 157: S32–8.Google ScholarPubMed
16Dobbelsteyn, CJ, Joffres, MR, MacLean, DR, Flowerdew, G and the Canadian Heart Surveys Research Group. A comparative evaluation of waist circumference, waist-to-hip ratio and body mass index as indicators of cardiovascular risk factors: The Canadian Heart Health Surveys. International Journal of Obesity and Related Metabolic Disorders 2001; 25: 652–61.CrossRefGoogle ScholarPubMed
17Seidell, JC, Cigolini, M, Charzewska, J, Ellsingen, BM, di-Biase, G. Fat distribution in European women: a comparison of anthropometric measurements in relation to cardiovascular risk factors. International Journal of Epidemiology 1990; 19: 303–8.CrossRefGoogle ScholarPubMed
18Woo, J, Ho, SC, Yu, AL, Sham, A. Is waist circumference a useful measure in predicting health outcomes in the elderly? International Journal of Obesity and Related Metabolic Disorders 2002; 26: 1349–55.CrossRefGoogle ScholarPubMed
19Molarius, A, Seidell, JC. Selection of anthropometric indicators for classification of abdominal fatness – a critical review. International Journal of Obesity and Related Metabolic Disorders 1998; 22: 719–27.CrossRefGoogle ScholarPubMed
20Gallagher, D, Visser, M, Sepulveda, D, Pierson, RN, Harris, T, Heymsfield, SB. How useful is body mass index for comparison of body fatness across age, sex and ethnic groups? American Journal of Epidemiology 1996; 143: 228–39.CrossRefGoogle ScholarPubMed
21Azizi, F, Rahmani, M, Emami, H, Majid, M. Tehran Lipid and Glucose Study: rationale and design. CVD Prevention 2000; 3: 242–7.Google Scholar
22Azizi, F, Emami, H, Salehi, P, Ghanbarian, A, Mirmiran, P, Mirbolooki, M. Cardiovascular risk factors in the elderly: the Tehran Lipid and Glucose Study. Journal of Cardiovascular Risk 2003; 10: 65–73.CrossRefGoogle ScholarPubMed
23Mirmiran, P, Mohammadi, F, Allahverdian, S, Azizi, F. Estimation of energy requirements for adults: Tehran Lipid and Glucose Study. International Journal for Vitamin and Nutrition Research 2003; 73: 193–200.CrossRefGoogle ScholarPubMed
24Mirmiran, P, Mohammadi, F, Allahverdian, S, Azizi, F. Association of educational level and marital status with dietary intake and cardiovascular risk factors in Tehranian adults: Tehran Lipid and Glucose Study. Nutrition Research 2002; 22: 1365–75.CrossRefGoogle Scholar
25Wang, J, Thornton, JC, Bari, S, Williamson, B, Gallagher, D, Heymsfield, SB. Comparisons of waist circumferences measured at 4 sites. American Journal of Clinical Nutrition 2003; 77: 379–84.CrossRefGoogle ScholarPubMed
26Friedewald, WT, Levy, RI, Fredrickson, DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clinical Chemistry 1972; 18: 499–502.CrossRefGoogle ScholarPubMed
27National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Circulation 2002; 106: 3143–421.CrossRefGoogle Scholar
28Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure. The sixth report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure. Archives of Internal Medicine 1997; 157: 2413–46.CrossRefGoogle Scholar
29Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 1997; 20: 1183–97.CrossRefGoogle Scholar
30Ross, R, Shaw, KD, Martel, Y, de Guise, J, Avruch, L. Adipose tissue distribution measured by magnetic resonance imaging in obese women. American Journal of Clinical Nutrition 1993; 67: 470–5.CrossRefGoogle Scholar
31Larsson, B, Svardsudd, K, Welin, L, Wilhelmsen, L, Bjorntorp, P, Tibblin, G. Abdominal adipose tissue distribution, obesity, and risk of cardiovascular disease and death: 13 year follow up of participants in the study of men born in 1913. British Medical Journal 1984; 288: 1401–4.CrossRefGoogle Scholar
32Schmidt, MI, Watson, RL, Duncan, BB, Metcalf, P, Brancati, FL, Sharrett, AR, et al. Clustering of dyslipidemia, hyperuricemia, diabetes, and hypertension and its association with fasting insulin and central and overall obesity in a general population: Atherosclerosis Risk in Communities Study Investigators. Metabolism 1996; 45: 699–706.CrossRefGoogle Scholar
33Zhu, S, Wang, Z, Heshka, S, Heo, M, Faith, MS, Heymsfield, SB. Waist circumference and obesity-associated risk factors among whites in the third National Health and Nutrition Examination Survey: clinical action thresholds. American Journal of Clinical Nutrition 2002; 76: 743–9.CrossRefGoogle ScholarPubMed
34Hwu, CM, Fuh, JL, Hsiao, CF, Wang, SJ, Lu, SR, Wei, MC, et al. Waist circumference predicts metabolic cardiovascular risk in postmenopausal Chinese women. Menopause 2003; 10: 73–80.Google ScholarPubMed
35Pelt, RE, Evans, EM, Schechtman, KB, Ehsani, AA, Kohrt, WM. Waist circumference vs body mass index for prediction of disease risk in postmenopausal women. International Journal of Obesity and Related Metabolic Disorders 2001; 25: 1183–8.CrossRefGoogle ScholarPubMed
36Foucan, L, Hanley, J, Deloumeaux, J, Suissa, S. Body mass index and waist circumference as screening tools for cardiovascular risk factors in Guadeloupean women. Journal of Clinical Epidemiology 2002; 55: 990–6.CrossRefGoogle ScholarPubMed
37Lin, WY, Lee, LT, Chen, CY, Lo, H, Hsia, HH, Liu, IL, et al. Optimal cut-off values for obesity: using simple anthropometric indices to predict cardiovascular risk factors in Taiwan. International Journal of Obesity and Related Metabolic Disorders 2002; 26: 1232–8.CrossRefGoogle ScholarPubMed
38Hsieh, SD, Yoshinaga, H. Waist/height ratio as a simple and useful predictor of coronary heart disease risk factors in women. Internal Medicine 1995; 34: 1147–52.CrossRefGoogle ScholarPubMed
39Ito, H, Nakasuga, K, Ohshima, A, Maruyama, T, Kaji, Y, Harada, M, et al. Detection of cardiovascular risk factors by indices of obesity obtained from anthropometry and dual-energy X-ray absorptiometry in Japanese individuals. International Journal of Obesity and Related Metabolic Disorders 2003; 27: 232–7.CrossRefGoogle ScholarPubMed
40Kortelainen, ML, Sarkioja, T. Coronary atherosclerosis and myocardial hypertrophy in relation to body fat distribution in healthy women: an autopsy study on 33 violent deaths. International Journal of Obesity and Related Metabolic Disorders 1997; 21: 43–9.CrossRefGoogle Scholar
41Shetterly, SM, Marshall, JA, Baxter, J, Hamman, RF. Waist–hip ratio measurement location influences associations with measures of glucose and lipid metabolism: The San Luis Valley Diabetes Study. Annals of Epidemiology 1993; 3: 295–9.CrossRefGoogle ScholarPubMed
42Lear, SA, Chen, MM, Frohlich, JJ, Birmingham, CL. The relationship between waist circumference and metabolic risk factors: cohorts of European and Chinese descent. Metabolism 2002; 51: 1427–32.CrossRefGoogle ScholarPubMed
43Daniel, M, Marion, SA, Sheps, SB, Hertzman, C, Gamble, D. Variation by body mass index and age in waist-to-hip ratio associations with glycemic status in an aboriginal population at risk for type 2 diabetes in British Columbia, Canada. American Journal of Clinical Nutrition 1999; 69: 455–60.CrossRefGoogle Scholar
44Allison, DB, Paultre, F, Goran, MI, Poehlman, ET, Heymsfield, SB. Statistical considerations regarding the use of ratios to adjust data. International Journal of Obesity and Related Metabolic Disorders 1995; 19: 644–52.Google ScholarPubMed
45Derpres, JP. The insulin resistance–dyslipidemic syndrome of visceral obesity: effect on patients' risk. Obesity Research 1998; 6: 85–175.Google Scholar
46Edwards, KL, Austin, MA, Newman, B, Mayer, E, Krauss, RM, Selby, JV. Multivariate analysis of the insulin resistance syndrome in women. Arteriosclerosis and Thrombosis 1994; 14: 1940–5.CrossRefGoogle ScholarPubMed
47den Tonkelaar, I, Seidell, JC, Collette, HJ. Body fat distribution in relation to breast cancer in women participating in the DOM-project. Breast Cancer Research and Treatment 1995; 34: 55–61.CrossRefGoogle ScholarPubMed
48Chumlea, NC, Kuczmarski, RJ. Using a bony landmark to measure waist circumference. Journal of the American Dietetic Association 1995; 95: 12.CrossRefGoogle ScholarPubMed
49National Heart, Lung, and Blood Institute. Clinical Guidelines on the Identification, Evaluation and Treatment of Overweight and Obesity in Adults – The Evidence Report. National Institutes of Health. Obesity Research 1998; 6: 51S–209S.Google Scholar
50Esmaillzadeh, A, Mirmiran, P, Azizi, F. Waist-to-hip ratio is a better screening measure for cardiovascular risk factors compared to other anthropometric indicators in Tehranian adult men. International Journal of Obesity and Related Metabolic Disorders 2004; 28: 1325–32.CrossRefGoogle ScholarPubMed
51Lear, SA, Chen, MM, Birmingham, CL, Frohlich, JJ. The relationship between simple anthropometric indices and C-reactive protein: ethnic and gender differences. Metabolism 2003; 52: 1542–6.CrossRefGoogle ScholarPubMed